Aircraft component maintenance quotation method, device and equipment and storage medium

The invention discloses a quotation method, device and equipment for aircraft component maintenance and a storage medium, and the method comprises the steps: obtaining historical damage data of an aircraft component, taking a corresponding damage type as a label, obtaining training sample data, and training a preset damage prediction model; wherein a data analysis method adopted by the damage prediction model comprises variance analysis, binary logistic regression, random forest impact factors and a BP neural network; inputting information of a to-be-maintained part into the trained damage prediction model to obtain damage pre-judgment information, and calling corresponding work card information in a work card database to obtain a maintenance pre-price; and when the to-be-maintained part is subjected to actual damage declaration, calling corresponding work card information according to the actual damage information to obtain a final maintenance quotation. According to the method, accurate damage analysis is r